Solution Architect – AI, Automation & Finance Transformation

Hewlett Packard Enterprise • Spring, TX

2d • $157,000 - $361,000 • Onsite

About The Position

Hewlett Packard Enterprise is hiring a Solution Architect to own end-to-end architecture for enterprise AI, automation and analytics solutions across its Finance Transformation portfolio. The architect defines target-state architecture and roadmaps, selects platforms and patterns, obtains enterprise technology, security and data governance approvals, and stays involved in delivery to ensure implementations conform to the approved design. The role translates Finance and Operations needs—including forecasting, reporting, reconciliation, transfer pricing, deal support and backlog analytics—into scalable, secure, governable and supportable solutions. It combines architecture leadership with hands-on technical work, including coding and personally building proofs of concept, while guiding engineers and vendors through implementation.

The position covers enterprise architecture artefacts and governance; AI, GenAI, agentic AI, machine learning and automation design; data and integration architecture; identity and access controls; deployment practices; and controls for financial data. It includes designing solutions on Microsoft Azure, GreenLake and Databricks, and integrating with platforms such as SAP, Salesforce, Anaplan, ServiceNow and Power BI. The architect leads technical delivery, supports production stabilisation and root-cause analysis, mentors teams, engages business and technology stakeholders, and advises portfolio planning.

Candidates should have at least ten years of experience in software engineering, data or AI, including at least three years in solution architecture or technical leadership, and recent enterprise delivery experience with GenAI or agentic AI. A bachelor's or master's degree in a related discipline is requested, though equivalent industry experience will be considered. The role is designated onsite, with the expectation of primarily working from an HPE office. The stated U.S. base salary range for Texas is USD 157,000–361,000 annually; variable incentives may also be offered. HPE describes benefits supporting physical, financial and emotional wellbeing, as well as personal and professional development programs.

Requirements

• At least ten years of experience in software engineering, data or AI, including at least three years in a solution architecture or technical lead capacity.
• A track record of architecting and delivering multiple enterprise solutions into production and through post-release support.
• Recent hands-on delivery of GenAI or agentic AI solutions in an enterprise setting.
• Bachelor's or master's degree in Computer Science, Information Technology, Engineering, Data Science or a related discipline; equivalent industry experience will be considered.
• Demonstrable ownership of solution architecture for enterprise systems that reached production and remained in service.
• Strong command of integration architecture, API design, event-driven patterns and data architecture across transactional and analytical estates.
• Ability to produce architecture documentation and decision records that withstand enterprise architecture and security review.
• Experience designing for scale, resilience, performance, observability and cost, with evidence that designs held in production.
• Hands-on experience architecting and delivering enterprise GenAI or LLM solutions, including RAG, tool and function calling, and agentic orchestration.
• Working knowledge of agentic frameworks and platforms such as LangChain, LangGraph, Semantic Kernel, AutoGen, Copilot Studio or equivalent.
• Experience with Azure OpenAI or comparable enterprise LLM platforms, including evaluation, guardrails and cost management at scale.
• Understanding of the machine learning lifecycle, including feature engineering, training, deployment, monitoring and drift, sufficient to architect ML solutions and govern delivery teams.
• Experience with enterprise automation and RPA platforms, and judgement about when automation is preferable to an AI-first approach.
• Strong, current hands-on Python skills for prototyping, code review and production debugging.
• Strong SQL skills and practical experience with Databricks, cloud data warehouses and modern data pipelines.
• Solid grounding in Microsoft Azure services, containerisation, CI/CD and infrastructure-as-code practices.
• Working knowledge of Power BI, Power Platform and the Microsoft 365 ecosystem as delivery surfaces for Finance solutions.
• Experience delivering enterprise Finance solutions in areas such as forecasting, financial reporting, reconciliation, transfer pricing, deal desk, tax, or order and backlog analytics.
• Understanding of financial controls, audit expectations and governance constraints for systems handling financial data.
• Ability to think in systems and trade-offs while maintaining both enterprise-level perspective and implementation detail.
• Ability to make decisions with incomplete information, record reasoning and revise positions when evidence changes.
• Hands-on credibility and ability to earn engineers' respect through direct technical contribution.
• Effective communication with both senior Finance stakeholders and technical teams.
• Comfort with ambiguity and evolving requirements, and ability to shape defensible scope from open-ended problems.
• Willingness to say no or not yet, with reasoning and an alternative.
• Ownership beyond design, including accountability for production outcomes.

Nice To Haves

• Recognised architecture certification, such as Azure Solutions Architect Expert, Databricks or TOGAF.
• Experience establishing AI governance, model risk or responsible-AI frameworks in a regulated enterprise.
• Experience defining reusable platform capabilities or internal developer experience adopted across multiple teams.
• Exposure to FinOps and cloud cost optimisation for AI and data workloads.
• Experience working in a global organisation across multiple regions and time zones.

Responsibilities

• Own the target-state architecture and roadmap for AI, GenAI, agentic AI and automation solutions across the Finance Transformation portfolio.
• Produce enterprise-standard architecture artefacts, including context and component diagrams, integration and data-flow designs, sequence flows, non-functional requirements and architecture decision records.
• Make and defend build-versus-buy, platform-selection and pattern decisions, documenting trade-offs in cost, delivery time, supportability and risk.
• Define reusable reference architectures, solution patterns and shared components.
• Own non-functional design for performance, scalability, availability, cost, observability and supportability, and establish production acceptance thresholds.
• Run design reviews and technical governance forums and obtain enterprise architecture, security and data governance approvals.
• Maintain an up-to-date view of the solution landscape and prevent duplicate or divergent builds.
• Architect LLM and agentic solutions, including orchestration, tools and function calling, retrieval and grounding, memory and state, human-in-the-loop checkpoints and fallback behaviour.
• Design retrieval-augmented generation over enterprise content, including chunking, embedding, index design, source-of-truth selection, freshness and permission-trimmed retrieval.
• Define AI evaluation and assurance methods, including golden datasets, accuracy and groundedness measures, regression testing and go-live criteria.
• Design responsible-AI guardrails and controls for prompt injection, data leakage, hallucinations, PII, auditability and human approval boundaries.
• Set and revisit model strategy, including model selection, routing, versioning, cost and token management, and upgrades.
• Select appropriately among machine learning, deterministic automation, conventional applications and generative AI for each problem.
• Design data architecture for AI and analytics use cases, including sources, ingestion, curated layers, semantic models, lineage and refresh cadence.
• Architect solutions on Microsoft Azure, GreenLake and Databricks, choosing suitable compute, storage, orchestration and serving components.
• Design integration across enterprise platforms, including API, event and batch patterns, error handling, idempotency and reconciliation.
• Define identity, access and secrets architecture using Okta, Microsoft Entra ID, OAuth, managed identities and role-based access control, applying least privilege.
• Set deployment architecture across environments, including CI/CD, promotion paths, environment parity, configuration management and rollback strategy.
• Design financial-data controls and audit readiness, including SOX-aligned controls, evidence capture, segregation of duties and output-to-source traceability.
• Lead engineers, data teams and vendors through implementation; review designs and code against the agreed architecture and address drift early.
• Build proofs of concept to de-risk patterns and document reusable lessons and patterns.
• Break initiatives into deliverable increments with technical dependencies, sequencing and defensible estimates.
• Identify and quantify architectural risk, technical debt and single points of failure, and propose remediation paths.
• Support production stabilisation, lead root-cause analysis of significant technical failures and incorporate findings into architecture.
• Develop team capability through mentoring, code and design reviews, enablement sessions and written guidance.
• Work with Finance, Operations and Transformation leaders to understand business problems and challenge requirements that will not achieve intended outcomes.
• Present architecture, options, cost implications and risks to business and technology stakeholders.
• Partner with enterprise architecture, security, infrastructure, DataOps and compliance teams to secure approvals and align solutions with enterprise standards.
• Manage vendor and partner technical engagement, including assessment, scope definition, design review and acceptance of delivered work.
• Advise portfolio planning on feasibility, effort, sequencing and platform readiness across initiatives.

Benefits

• A comprehensive suite of benefits supporting physical, financial and emotional wellbeing for employees and their loved ones.
• Programs supporting personal and professional development and career goals.
• Variable incentives may be offered in addition to base salary.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior